Field of the Disclosure
The present disclosure relates generally to the field of data management, and specifically clinical trial data management.
Description of the Related Art
Before a new medical drug (e.g., pharmaceuticals), device (e.g., surgical instruments or implants), or procedure may be dispensed to the public, the United States Food and Drug Administration (FDA) requires that the manufacturers conduct extensive clinical trial research in order to demonstrate the clinical effectiveness, safety, and medical advantage of their products or procedures. Extensive and often complex clinical trial protocols are developed that define, for example, targeted demographics, proposed medications, patient regimens, forms for collection, types of statistically relevant data, the timing or order of events within the study, often even the layout of the reporting data, or other suitable data. These protocols are often sufficiently complex that the protocols themselves receive FDA approval or validation.
Once a protocol is developed and approved, companies design electronic data capture and data management solutions to manage the ever burgeoning amount of data gathered. In general, such data capture and data management solutions capture data from geographically disparate clinicians or study participants defining many points of data entry, potentially across many software and hardware platforms.
As one may suppose, manufacturers invest millions of dollars conducting the foregoing clinical trials before they receive any revenue from a sale of their products. For example, a rough estimate may be as long as 12 to 15 years to bring a drug to market at a cost of over $800 million. Accordingly, sponsors are eager to lower the cost and complexity associated with clinical trials, and sponsors are almost fanatical in their desire to avoid corruption of acquired clinical trial data. An entire industry of companies, called Contract Research Organizations (CROs), has developed that specialize in the execution of clinical trials and in the capture and management of clinical trial data on behalf of the manufacturers.
Whether performed by a CRO or by manufacturers themselves, the systems that acquire and manage clinical trial data often are also approved or validated by FDA. Such validation ensures that acquired clinical trial data is protected from fraud, corruption, software upgrade errors, and commingling. However, drawbacks occur when a system upgrade is desired even though one or more clinical trials may be years into execution within the system. For example, when something fails during an upgrade, or when an upgraded system fails to pass the FDA validation, the data for the already executing trials may be deemed corrupted. Clearly, such a finding of corruption can result in losses of millions of dollars in retesting, recollecting data, and perhaps most significant, can result in a significant loss of time. Moreover, even if the upgrade is successful, translation from an old system to the new upgraded system may include significant brute force computing to organize often vast amounts of collected data. Based simply on the possibility of harm to the existing data, manufacturers and CROs are often unwilling to upgrade systems where trials are in progress. Also, because trials can start at any time and have wildly varying durations, finding a time for upgrades may be impractical.
Based on the foregoing, manufacturers and CROs have begun to compartmentalize backend databases. Compartmentalization segments the various trials' data and each database can be upgraded individually. However, such systems are still exposed to corruption issues from, for example, code validations. Moreover, such a system increases complexity by allowing for code bases and database to be different upgrades or version for the same study.